Psychological Pathways to Immunity: The Role of Emotions and Stress in Health and Disease
Bibliographic record
Abstract
As we navigate the complexities of the human condition, it becomes increasingly clear that our mental health is inseparable from our physical health. The intricate dance between our psychological states and immune responses offers a compelling testament to the power of the mind over the body. By delving deeper into the mechanisms underlying this relationship, we can unlock new frontiers in our pursuit of health and well-being, emphasizing the need for a comprehensive approach to healthcare that honors the profound connection between our emotional landscape and our physical health. In conclusion, this article serves as a critical reminder of the intricate link between our psychological well-being and immune function. As research in this field continues to evolve, it holds the promise of transforming our approach to health and disease, advocating for a more nuanced understanding of the interplay between mind and body. In recognizing the powerful role of emotions and stress in modulating immunity, we pave the way for innovative strategies in health promotion and disease prevention, heralding a new era in holistic healthcare.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".